Radiologists use radiographic images such as mammograms to detect and pinpoint suspicious lesions in a patient as early as possible, e.g., before a disease is readily detectable by other, intrusive methods. As such, there is real benefit to the radiologist being able to locate, based on imagery, extremely small cancerous lesions and precursors. Microcalcifications, particularly those occurring in certain types of clusters, exemplify one signature of concern. Although the individual calcifications tend to readily absorb radiation and can thus appear quite bright in a radiographic image, various factors including extremely small size, occlusion by other natural structure, appearance in a structurally “busy” portion of the image, all sometimes coupled with radiologist fatigue, may make some calcifications hard to detect upon visual inspection.
Computer-Aided Detection (CAD) algorithms have been developed to assist radiologists in locating potential lesions in a radiographic image, including microcalcification clusters and masses. Some CAD vendors create a display and place a single mark at the center of a CAD-detected cluster or mass, which the radiologist can then select with a cursor to see a zoomed-in view of the area. Other vendors draw a larger, regular geometric shape on the display, centered on the abnormality, e.g., with a rectangle representing a mass and an ellipse indicating a microcalcification cluster.